[pre-commit.ci] pre-commit autoupdate (TheAlgorithms#12398)

updates:
- [github.com/astral-sh/ruff-pre-commit: v0.4.10 → v0.5.0](astral-sh/ruff-pre-commit@v0.4.10...v0.5.0)
- [github.com/pre-commit/mirrors-mypy: v1.10.0 → v1.10.1](pre-commit/mirrors-mypy@v1.10.0...v1.10.1)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: pre-commit-ci[bot]

.pre-commit-config.yaml

@@ -16,7 +16,7 @@ repos:
       - id: auto-walrus
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.7.4
+    rev: v0.8.0
     hooks:
       - id: ruff
       - id: ruff-format

cellular_automata/conways_game_of_life.py

@@ -58,10 +58,8 @@ def new_generation(cells: list[list[int]]) -> list[list[int]]:
             # 3. All other live cells die in the next generation.
             #    Similarly, all other dead cells stay dead.
             alive = cells[i][j] == 1
-            if (
-                (alive and 2 <= neighbour_count <= 3)
-                or not alive
-                and neighbour_count == 3
+            if (alive and 2 <= neighbour_count <= 3) or (
+                not alive and neighbour_count == 3
             ):
                 next_generation_row.append(1)
             else:

ciphers/playfair_cipher.py

@@ -24,7 +24,7 @@
 from collections.abc import Generator, Iterable
 
 
-def chunker(seq: Iterable[str], size: int) -> Generator[tuple[str, ...], None, None]:
+def chunker(seq: Iterable[str], size: int) -> Generator[tuple[str, ...]]:
     it = iter(seq)
     while True:
         chunk = tuple(itertools.islice(it, size))

ciphers/simple_keyword_cypher.py

@@ -10,7 +10,7 @@ def remove_duplicates(key: str) -> str:
 
     key_no_dups = ""
     for ch in key:
-        if ch == " " or ch not in key_no_dups and ch.isalpha():
+        if ch == " " or (ch not in key_no_dups and ch.isalpha()):
             key_no_dups += ch
     return key_no_dups
 

ciphers/transposition_cipher.py

@@ -52,10 +52,8 @@ def decrypt_message(key: int, message: str) -> str:
         plain_text[col] += symbol
         col += 1
 
-        if (
-            (col == num_cols)
-            or (col == num_cols - 1)
-            and (row >= num_rows - num_shaded_boxes)
+        if (col == num_cols) or (
+            (col == num_cols - 1) and (row >= num_rows - num_shaded_boxes)
         ):
             col = 0
             row += 1

compression/lempel_ziv.py

@@ -35,8 +35,8 @@ def add_key_to_lexicon(
     lexicon[curr_string + "0"] = last_match_id
 
     if math.log2(index).is_integer():
-        for curr_key in lexicon:
-            lexicon[curr_key] = "0" + lexicon[curr_key]
+        for curr_key, value in lexicon.items():
+            lexicon[curr_key] = f"0{value}"
 
     lexicon[curr_string + "1"] = bin(index)[2:]
 

data_structures/arrays/sudoku_solver.py

@@ -156,7 +156,7 @@ def time_solve(grid):
     times, results = zip(*[time_solve(grid) for grid in grids])
     if (n := len(grids)) > 1:
         print(
-            "Solved %d of %d %s puzzles (avg %.2f secs (%d Hz), max %.2f secs)."
+            "Solved %d of %d %s puzzles (avg %.2f secs (%d Hz), max %.2f secs)."  # noqa: UP031
             % (sum(results), n, name, sum(times) / n, n / sum(times), max(times))
         )
 

data_structures/binary_tree/binary_tree_traversals.py

@@ -30,7 +30,7 @@ def make_tree() -> Node | None:
     return tree
 
 
-def preorder(root: Node | None) -> Generator[int, None, None]:
+def preorder(root: Node | None) -> Generator[int]:
     """
     Pre-order traversal visits root node, left subtree, right subtree.
     >>> list(preorder(make_tree()))
@@ -43,7 +43,7 @@ def preorder(root: Node | None) -> Generator[int, None, None]:
     yield from preorder(root.right)
 
 
-def postorder(root: Node | None) -> Generator[int, None, None]:
+def postorder(root: Node | None) -> Generator[int]:
     """
     Post-order traversal visits left subtree, right subtree, root node.
     >>> list(postorder(make_tree()))
@@ -56,7 +56,7 @@ def postorder(root: Node | None) -> Generator[int, None, None]:
     yield root.data
 
 
-def inorder(root: Node | None) -> Generator[int, None, None]:
+def inorder(root: Node | None) -> Generator[int]:
     """
     In-order traversal visits left subtree, root node, right subtree.
     >>> list(inorder(make_tree()))
@@ -69,7 +69,7 @@ def inorder(root: Node | None) -> Generator[int, None, None]:
     yield from inorder(root.right)
 
 
-def reverse_inorder(root: Node | None) -> Generator[int, None, None]:
+def reverse_inorder(root: Node | None) -> Generator[int]:
     """
     Reverse in-order traversal visits right subtree, root node, left subtree.
     >>> list(reverse_inorder(make_tree()))
@@ -93,7 +93,7 @@ def height(root: Node | None) -> int:
     return (max(height(root.left), height(root.right)) + 1) if root else 0
 
 
-def level_order(root: Node | None) -> Generator[int, None, None]:
+def level_order(root: Node | None) -> Generator[int]:
     """
     Returns a list of nodes value from a whole binary tree in Level Order Traverse.
     Level Order traverse: Visit nodes of the tree level-by-level.
@@ -116,9 +116,7 @@ def level_order(root: Node | None) -> Generator[int, None, None]:
             process_queue.append(node.right)
 
 
-def get_nodes_from_left_to_right(
-    root: Node | None, level: int
-) -> Generator[int, None, None]:
+def get_nodes_from_left_to_right(root: Node | None, level: int) -> Generator[int]:
     """
     Returns a list of nodes value from a particular level:
     Left to right direction of the binary tree.
@@ -128,7 +126,7 @@ def get_nodes_from_left_to_right(
     [2, 3]
     """
 
-    def populate_output(root: Node | None, level: int) -> Generator[int, None, None]:
+    def populate_output(root: Node | None, level: int) -> Generator[int]:
         if not root:
             return
         if level == 1:
@@ -140,9 +138,7 @@ def populate_output(root: Node | None, level: int) -> Generator[int, None, None]
     yield from populate_output(root, level)
 
 
-def get_nodes_from_right_to_left(
-    root: Node | None, level: int
-) -> Generator[int, None, None]:
+def get_nodes_from_right_to_left(root: Node | None, level: int) -> Generator[int]:
     """
     Returns a list of nodes value from a particular level:
     Right to left direction of the binary tree.
@@ -152,7 +148,7 @@ def get_nodes_from_right_to_left(
     [3, 2]
     """
 
-    def populate_output(root: Node | None, level: int) -> Generator[int, None, None]:
+    def populate_output(root: Node | None, level: int) -> Generator[int]:
         if not root:
             return
         if level == 1:
@@ -164,7 +160,7 @@ def populate_output(root: Node | None, level: int) -> Generator[int, None, None]
     yield from populate_output(root, level)
 
 
-def zigzag(root: Node | None) -> Generator[int, None, None]:
+def zigzag(root: Node | None) -> Generator[int]:
     """
     ZigZag traverse:
     Returns a list of nodes value from left to right and right to left, alternatively.

data_structures/linked_list/deque_doubly.py

@@ -12,7 +12,7 @@ class _DoublyLinkedBase:
     """A Private class (to be inherited)"""
 
     class _Node:
-        __slots__ = "_prev", "_data", "_next"
+        __slots__ = "_data", "_next", "_prev"
 
         def __init__(self, link_p, element, link_n):
             self._prev = link_p

data_structures/queue/double_ended_queue.py

@@ -33,7 +33,7 @@ class Deque:
         the number of nodes
     """
 
-    __slots__ = ("_front", "_back", "_len")
+    __slots__ = ("_back", "_front", "_len")
 
     @dataclass
     class _Node:

docs/source/__init__.py

@@ -6,7 +6,7 @@
 
 from __future__ import annotations
 
-from math import pow, sqrt
+from math import pow, sqrt  # noqa: A004
 
 
 def electrical_impedance(

electronics/electrical_impedance.py

@@ -194,10 +194,8 @@ def city_select(
     IndexError: list index out of range
     """
     probabilities = []
-    for city in unvisited_cities:
-        city_distance = distance(
-            unvisited_cities[city], next(iter(current_city.values()))
-        )
+    for city, value in unvisited_cities.items():
+        city_distance = distance(value, next(iter(current_city.values())))
         probability = (pheromone[city][next(iter(current_city.keys()))] ** alpha) * (
             (1 / city_distance) ** beta
         )

graphs/ant_colony_optimization_algorithms.py

@@ -133,18 +133,18 @@ def dijk(g, s):
         if len(known) == len(g) - 1:
             break
         mini = 100000
-        for i in dist:
-            if i not in known and dist[i] < mini:
-                mini = dist[i]
-                u = i
+        for key, value in dist:
+            if key not in known and value < mini:
+                mini = value
+                u = key
         known.add(u)
         for v in g[u]:
             if v[0] not in known and dist[u] + v[1] < dist.get(v[0], 100000):
                 dist[v[0]] = dist[u] + v[1]
                 path[v[0]] = u
-    for i in dist:
-        if i != s:
-            print(dist[i])
+    for key, value in dist.items():
+        if key != s:
+            print(value)
 
 
 """
@@ -255,10 +255,10 @@ def prim(g, s):
         if len(known) == len(g) - 1:
             break
         mini = 100000
-        for i in dist:
-            if i not in known and dist[i] < mini:
-                mini = dist[i]
-                u = i
+        for key, value in dist.items():
+            if key not in known and value < mini:
+                mini = value
+                u = key
         known.add(u)
         for v in g[u]:
             if v[0] not in known and v[1] < dist.get(v[0], 100000):

graphs/basic_graphs.py

@@ -185,12 +185,12 @@ def boruvka_mst(graph):
 
                     if cheap_edge[set2] == -1 or cheap_edge[set2][2] > weight:
                         cheap_edge[set2] = [head, tail, weight]
-            for vertex in cheap_edge:
-                if cheap_edge[vertex] != -1:
-                    head, tail, weight = cheap_edge[vertex]
+            for head_tail_weight in cheap_edge.values():
+                if head_tail_weight != -1:
+                    head, tail, weight = head_tail_weight
                     if union_find.find(head) != union_find.find(tail):
                         union_find.union(head, tail)
-                        mst_edges.append(cheap_edge[vertex])
+                        mst_edges.append(head_tail_weight)
                         num_components = num_components - 1
         mst = Graph.build(edges=mst_edges)
         return mst

graphs/minimum_spanning_tree_boruvka.py

@@ -131,7 +131,7 @@ def preprocess(message: bytes) -> bytes:
     return bit_string
 
 
-def get_block_words(bit_string: bytes) -> Generator[list[int], None, None]:
+def get_block_words(bit_string: bytes) -> Generator[list[int]]:
     """
     Splits bit string into blocks of 512 chars and yields each block as a list
     of 32-bit words

hashes/md5.py

@@ -107,8 +107,8 @@ def create_tree(data_set: list, min_sup: int = 1) -> tuple[TreeNode, dict]:
     if not (freq_item_set := set(header_table)):
         return TreeNode("Null Set", 1, None), {}
 
-    for k in header_table:
-        header_table[k] = [header_table[k], None]
+    for key, value in header_table.items():
+        header_table[key] = [value, None]
 
     fp_tree = TreeNode("Null Set", 1, None)  # Parent is None for the root node
     for tran_set in data_set:

machine_learning/frequent_pattern_growth.py

@@ -17,7 +17,7 @@
 from collections.abc import Generator
 
 
-def collatz_sequence(n: int) -> Generator[int, None, None]:
+def collatz_sequence(n: int) -> Generator[int]:
     """
     Generate the Collatz sequence starting at n.
     >>> tuple(collatz_sequence(2.1))

maths/collatz_sequence.py

@@ -2,7 +2,7 @@
 from collections.abc import Generator
 
 
-def slow_primes(max_n: int) -> Generator[int, None, None]:
+def slow_primes(max_n: int) -> Generator[int]:
     """
     Return a list of all primes numbers up to max.
     >>> list(slow_primes(0))
@@ -29,7 +29,7 @@ def slow_primes(max_n: int) -> Generator[int, None, None]:
             yield i
 
 
-def primes(max_n: int) -> Generator[int, None, None]:
+def primes(max_n: int) -> Generator[int]:
     """
     Return a list of all primes numbers up to max.
     >>> list(primes(0))
@@ -58,7 +58,7 @@ def primes(max_n: int) -> Generator[int, None, None]:
             yield i
 
 
-def fast_primes(max_n: int) -> Generator[int, None, None]:
+def fast_primes(max_n: int) -> Generator[int]:
     """
     Return a list of all primes numbers up to max.
     >>> list(fast_primes(0))

maths/prime_numbers.py

@@ -6,7 +6,7 @@
 
 from __future__ import annotations
 
-from math import pi, pow
+from math import pi, pow  # noqa: A004
 
 
 def vol_cube(side_length: float) -> float:

maths/volume.py

@@ -61,9 +61,8 @@ def _extract_images(f):
     with gzip.GzipFile(fileobj=f) as bytestream:
         magic = _read32(bytestream)
         if magic != 2051:
-            raise ValueError(
-                "Invalid magic number %d in MNIST image file: %s" % (magic, f.name)
-            )
+            msg = f"Invalid magic number {magic} in MNIST image file: {f.name}"
+            raise ValueError(msg)
         num_images = _read32(bytestream)
         rows = _read32(bytestream)
         cols = _read32(bytestream)
@@ -102,9 +101,8 @@ def _extract_labels(f, one_hot=False, num_classes=10):
     with gzip.GzipFile(fileobj=f) as bytestream:
         magic = _read32(bytestream)
         if magic != 2049:
-            raise ValueError(
-                "Invalid magic number %d in MNIST label file: %s" % (magic, f.name)
-            )
+            msg = f"Invalid magic number {magic} in MNIST label file: {f.name}"
+            raise ValueError(msg)
         num_items = _read32(bytestream)
         buf = bytestream.read(num_items)
         labels = np.frombuffer(buf, dtype=np.uint8)

neural_network/input_data.py

@@ -1,7 +1,3 @@
-from math import pow, sqrt
-
-from scipy.constants import G, c, pi
-
 """
 These two functions will return the radii of impact for a target object
 of mass M and radius R as well as it's effective cross sectional area sigma.
@@ -14,9 +10,12 @@
 cross section for capture as sigma=π*R_capture**2.
 
 This algorithm does not account for an N-body problem.
-
 """
 
+from math import pow, sqrt  # noqa: A004
+
+from scipy.constants import G, c, pi
+
 
 def capture_radii(
     target_body_radius: float, target_body_mass: float, projectile_velocity: float

physics/basic_orbital_capture.py

@@ -14,7 +14,7 @@
 (Description adapted from https://en.wikipedia.org/wiki/Graham%27s_law)
 """
 
-from math import pow, sqrt
+from math import pow, sqrt  # noqa: A004
 
 
 def validate(*values: float) -> bool:

physics/grahams_law.py

@@ -27,7 +27,7 @@
 from collections.abc import Generator
 
 
-def fibonacci_generator() -> Generator[int, None, None]:
+def fibonacci_generator() -> Generator[int]:
     """
     A generator that produces numbers in the Fibonacci sequence